Mark is a general manager of a large sporting goods national chain. He manages aDenver store with 50 employees. To keep track of different products that have unique characteristics and coding, Mark sets up multiple inventory databases within his ownstore. At the end of every quarter, he combines the different databases and analyzes trends for his regular report to national. What type of database system is Markusing to create his report?
A.
Data warehouse
B.
Data mart
C.
Data storage
D.
Data mine
Explanation:
A data mart is a subset of an organizational data store, usuallyoriented to a specific purpose or major data subject, that may be distributed tosupport business needs. Data marts are analytical data stores designed to focus onspecific business functions for a specific community within an organization.
A data mart is the access layer of the data warehouse environment that is used to get data out to the users. The data mart is a subset of the data warehouse that is usually oriented to a specific business line or team. Data marts are small slices of the data warehouse. Whereas data warehouses have an enterprise-wide depth, the information in data marts pertains to a single department. In some deployments, each department or business unit is considered the owner of its data mart including all the hardware, software and data.[1] This enables each department to use, manipulate and develop their data any way they see fit; without altering information inside other data marts or the data warehouse. In other deployments where conformed dimensions are used, this business unit ownership will not hold true for shared dimensions like customer, product, etc.
The reasons why organizations are building data warehouses and data marts are because the information in the database is not organized in a way that makes it easy for organizations to find what they need. Also complicated queries might take a long time to answer what people want to know since the database systems are designed to process millions of transactions per day. Transactional database are designed to be updated, however, data warehouses or marts are read only. Data warehouses are designed to access large groups of related records.
Data marts improve end-user response time by allowing users to have access to the specific type of data they need to view most often by providing the data in a way that supports the collective view of a group of users.
A data mart is basically a condensed and more focused version of a data warehouse that reflects the regulations and process specifications of each business unit within an organization. Each data mart is dedicated to a specific business function or region. This subset of data may span across many or all of an enterprise’s functional subject areas. It is common for multiple data marts to be used in order to serve the needs of each individual business unit (different data marts can be used to obtain specific information for various enterprise departments, such as accounting, marketing, sales, etc.).
The related term spreadmart is a derogatory label describing the situation that occurs when one or more business analysts develop a system of linked spreadsheets to perform a business analysis, then grow it to a size and degree of complexity that makes it nearly impossible to maintain.
The primary use for a data mart is business intelligence (BI) applications. BI is used to gather, store, access and analyze data. The data mart can be used by smaller businesses to utilize the data they have accumulated. A data mart can be less expensive than implementing a data warehouse, thus making it more practical for the small business. A data mart can also be set up in much less time than a data warehouse, being able to be set up in less than 90 days. Since most small businesses only have use for a small number of BI applications, the low cost and quick set up of the data mart makes it a suitable method for storing data.[2]